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Electrophysiological Receptor Mapping of GABAA Receptors

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Electrophysiological Receptor Mapping of GABAA Receptors bioRxiv preprint doi: https://doi.org/10.1101/2020.05.11.087726; this version posted May 12, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Electrophysiological receptor mapping of GABAA receptors Alexander D Shaw1, Hannah Chandler1, Khalid Hamandi1, Suresh D Muthukumaraswamy2, Alexander Hammers3, Krish D Singh1. 1Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, CF24 4HQ 2School of Pharmacy, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand 3 School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London SE1 7EH Corresponding Author: Dr Alexander D Shaw1, [email protected] Word counts: Abstract: 342 Introduction: 819 Methods: 1257 Results: 1000 Discussion: 968 Figures: 9 Tables: 0 Supplementary Materials: Yes Declarations: none. bioRxiv preprint doi: https://doi.org/10.1101/2020.05.11.087726; this version posted May 12, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Abstract The non-invasive study of cortical oscillations provides a window onto neuronal processing. Temporal correlation of these oscillations between distinct anatomical regions is considered a marker of functional connectedness. As the most abundant inhibitory neurotransmitter in the mammalian brain, γ-aminobutyric acid (GABA) is thought to play a crucial role in shaping the frequency and amplitude of oscillations, which thereby suggests a further role for GABA in shaping the topography of functional connectivity. This study explored the effects of pharmacologically blocking the reuptake of GABA (increasing local concentrations and availability) through oral administration of the GAT1-blocker tiagabine (15 mg). We show that the spatial distribution of connectivity effects corresponds to template maps of flumazenil PET maps of GABAA receptor distribution. In a placebo-controlled crossover design, we collected resting MEG recordings from 15 healthy male individuals prior to, and at 1-, 3- and 5- hours post, administration of tiagabine and placebo pill. Using amplitude envelope correlations (AECs) we quantified the functional connectivity in discrete frequency bands across the whole brain, using the 90-region Automatic Anatomical Labelling atlas (AAL90), as well as quantifying the average oscillatory activity at each region. Analysis of variance in connectivity using a drug-by-time (2x4) design revealed interaction effects, accompanied by main effects of drug and time. Post-hoc permutation testing of each post-drug recording against the respective pre-drug baseline revealed consistent reductions of a bilateral occipital network spanning theta, alpha and beta frequencies, and across 1- 3- and 5- hour recordings following tiagabine, but not placebo. The same analysis applied to the activity of each region also revealed a significant interaction, with post-hoc permutation testing signalling significant reductions in activity in middle occipital regions across delta, theta, alpha and beta frequency bands. Crucially, we show that the spatial distribution of both connectivity and activity changes with tiagabine overlaps significantly with template quantitative GABAA maps derived from flumazenil volume-of- distribution (FMZ-VT) PET, clearly demonstrating a mechanistic link between GABA availability, GABAA receptor distribution and low-frequency network oscillations. We therefore propose a utility for functional connectivity and activity measures as receptor-mapping tools in pharmacological imaging. Introduction Oscillations measured using non-invasive methods, such as magnetoencephalography (MEG), arise from the synchronous oscillatory-activation of post-synaptic currents in ensembles of principal cells in cortex (Brunel & Wang, 2003; Buzsáki et al., 2004; Wang, 2010), predominantly those in superficial layers (Buzsáki et al., 2012; Xing et al., 2012). Converging evidence from experimental (Kramer et al., bioRxiv preprint doi: https://doi.org/10.1101/2020.05.11.087726; this version posted May 12, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 2008; M. a Whittington et al., 1995) and computational (Brunel & Wang, 2003; Pinotsis et al., 2013; Shaw et al., 2017) studies suggests that the attributes of these oscillations – the peak frequency and amplitude – are determined by more fundamental, unobserved, neurophysiological processes. For example, the peak frequency of oscillations within the alpha range (8 – 13 Hz) may be a mechanistic consequence of synchronised firing (action potentials) at the same rate (Halgren et al., 2017; Lorincz et al., 2009), while the peak frequency of oscillations across many frequency bands has been linked with inhibitory neurotransmission (Buzsáki et al., 2004; Hall et al., 2011; Roopun et al., 2006; M. A. Whittington et al., 2000) mediated by γ-aminobutyric acid (GABA). The link between GABA and macroscopic oscillations observed in MEG is likely mediated by the functional inhibitory role of GABA receptors, which are broadly categorised as fast, ionotropic GABAA and slower g-protein coupled GABAB, although there exist subtypes of each (Belelli et al., 2009; Vargas, 2018; Whiting, 2003). The currents mediated by both of these receptor types have been implicated in oscillation generation through control of recurrent excitatory-inhibition (Atallah & Scanziani, 2009; Brunel & Wang, 2003; Galarreta & Hestrin, 1998; Kohl & Paulsen, 2010; Krupa et al., 2014), whereby the GABAergically-mediated inhibitory currents exert temporal control over the firing and activity of excitatory principal cells (Bartos et al., 2007; M. A. Whittington et al., 2000). In the case of higher-frequency oscillations, including beta (13 - 30 Hz) and gamma (30+ Hz), the peak frequency may be dependent on the balance of excitatory and inhibitory currents (Brunel & Wang, 2003; Kujala et al., 2015; Shaw et al., 2017), implicating excitatory glutamatergic receptor types, such as α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) and N-methyl-D-aspartate (NMDA). Pharmaco-MEG studies provide a framework for examining the effects that pharmacologically manipulating neurotransmitter or neuromodulator systems has on oscillatory activity. Studies of GABAergic drugs to date have primarily examined changes in task-induced fluctuations in oscillation metrics, usually confined to the analysis of one particular sensory system. For example in the motor cortex, diazepam, a benzodiazepine, facilitates the amplitude of movement-related beta desynchrony (MRBD) (Hall et al., 2011). In visual cortex, propofol, an agonist of GABAA receptors, increased the amplitude of gamma oscillations and concurrently suppressed the amplitude of alpha oscillations (Saxena et al., 2013). Alcohol, which has a complex binding profile including benzodiazepine- mediated GABAA effects, decreased the frequency and increased the amplitude of gamma in the visual cortex (Campbell et al., 2014). For other GABAergic pharmaco-MEG summaries, see ((Suresh D Muthukumaraswamy, 2014; Nutt et al., 2015)) These studies clearly demonstrate a role for GABA in shaping oscillatory responses, however they are confined to observations of task-related, local dynamics. Non-task induced recordings of oscillatory activity, at ‘resting state’, focus on correlation of fluctuations in different brain regions, within specific frequency bands. This ‘functional connectivity’ approach rests on the assumption that discrete regions of the brain whose band-limited amplitude bioRxiv preprint doi: https://doi.org/10.1101/2020.05.11.087726; this version posted May 12, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. envelopes are correlated, are functionally connected. Since GABA plays a role in shaping the oscillations of local (within-region), task-induced dynamics, it is expected that it also shapes the topography of the networks formed by these regions interacting. No pharmaco-MEG studies have examined GABAergic manipulation of functional connectivity across the brain, although studies examining other compounds have. Antagonism of NMDA receptors by ketamine decreased alpha and beta networks spanning motor, parietal and occipital regions (S. D. Muthukumaraswamy et al., 2015), while antagonism of AMPA receptors by perampanel increased alpha and beta in similar posterior visual and parietal regions (Routley et al., 2017). Comparison of the spatial distribution of these reductions with recent maps of receptor distributions (Zilles & Palomero-Gallagher, 2017) revealed that these areas also have higher-than-average densities of NMDA and AMPA receptors in superficial cortical layers, as well as higher-than-average densities of GABAA and GABAB receptors (where the average is calculated over the 44 cortex-wide regions tested) (Zilles
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